






"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case : Optional[Any]     		=		logging.get_logger(__name__)

snake_case : List[Any]     		=		{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}



class        UpperCamelCase__ (				a_):







    """simple docstring"""
    __UpperCAmelCase           = """mobilenet_v1"""







    def __init__(		self :	Union[str, Any]				,    UpperCamelCase_ :	Optional[Any]=3				,    UpperCamelCase_ :	Optional[Any]=2_2_4				,    UpperCamelCase_ :	List[Any]=1.0				,    UpperCamelCase_ :	Any=8				,    UpperCamelCase_ :	str="relu6"				,    UpperCamelCase_ :	int=True				,    UpperCamelCase_ :	Union[str, Any]=0.999				,    UpperCamelCase_ :	List[Any]=0.02				,    UpperCamelCase_ :	int=0.001				,    **UpperCamelCase_ :	Optional[int]				,    ):





           '''simple docstring'''

           super().__init__(**UpperCamelCase_ )

           if depth_multiplier <= 0:
                  raise ValueError('depth_multiplier must be greater than zero.' )

           __magic_name__      				=    num_channels
           __magic_name__      				=    image_size
           __magic_name__      				=    depth_multiplier
           __magic_name__      				=    min_depth
           __magic_name__      				=    hidden_act
           __magic_name__      				=    tf_padding
           __magic_name__      				=    classifier_dropout_prob
           __magic_name__      				=    initializer_range
           __magic_name__      				=    layer_norm_eps



class        UpperCamelCase__ (				a_):







    """simple docstring"""
    __UpperCAmelCase           = version.parse("""1.11""")







    @property
    def 				a__			(		self :	Union[str, Any] ):





           '''simple docstring'''

           return OrderedDict([('pixel_values', {0: 'batch'})] )







    @property
    def 				a__			(		self :	List[Any] ):





           '''simple docstring'''

           if self.task == "image-classification":
                  return OrderedDict([('logits', {0: 'batch'})] )
           else:
                  return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})] )







    @property
    def 				a__			(		self :	Union[str, Any] ):





           '''simple docstring'''

           return 1e-4







"""simple docstring"""
def 							A						(				__snake_case: int = 1_0_0_0_0_0_0  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    limit + 1
       __magic_name__      				=    [0] * limit
       for first_term in range(1 ,     __snake_case  ):
              for n in range(__snake_case ,     __snake_case ,     __snake_case  ):
                     __magic_name__      				=    first_term + n / first_term
                     if common_difference % 4:  # d must be divisble by 4
                            continue
                     else:
                            common_difference /= 4
                            if (
                                first_term > common_difference
                                and first_term < 4 * common_difference
                            ):  # since x,y,z are positive integers
                                   frequency[n] += 1  # so z>0 and a>d ,also 4d<a

       __magic_name__      				=    sum(1 for x in frequency[1:limit] if x == 1_0  )

       return count


if __name__ == "__main__":
 print(f"""{solution() = }""")